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This study considers a networked system in which the measurement suffers from one-step delay and packet dropouts because of the unreliability of the network. A new model applied to describe the arrival conditions of the measurements is proposed. Based on the new model and using a state augmentation method, optimal linear filter, predictor and smoother are obtained. A sufficient condition for the convergence of the system is given. Finally, the simulation results show the effectiveness of the proposed algorithms.

Cr 3+ -activated persistent luminescent phosphors with a spinel structure are emerging materials in bio-imaging applications for their distinctive features of deep biotissue penetration and rechargeable nearinfrared persistent emission. To realize the long-term and multicycle imaging purpose, reactivation using in situ external light with deep biotissue penetration is an alternative strategy, apart from the efforts on trap modulations for the host lattice. However, recharging with high-energy ultraviolet /visible photons will result in low activation efficiency because of the absorption by biological tissues. Here, we report a low-energy photonrechargeable near-infrared persistent material, with rechargeable efficiency 400 times higher than that of the ZnGa 2 O 4 :Cr 3+ reference material. The crystal field strength and band gap energies can be tailored by control of cation occupancy, contributing the red shift of both the persistent luminescence excitation and emission spectra of the optimized complex spinel samples. The persistent emission red shift is of interest for improved deep tissue penetration for bioimaging, whereas the persistent excitation red shift facilitates the activation of persistent luminescence by low-energy radiation. Furthermore, it demonstrates that increasing the rate of cation site inversion in the spinel can lead to higher storage capacity of charge trapping.

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Impaired spontaneous regional activity and altered topology of the brain network have been observed in obstructive sleep apnea (OSA). However, the mechanisms of disrupted functional connectivity (FC) and topological reorganization of the default mode network (DMN) in patients with OSA remain largely unknown. We explored whether the FC is altered within the DMN and examined topological changes occur in the DMN in patients with OSA using a graph theory analysis of resting-state functional magnetic resonance imaging data and evaluated the relationship between neuroimaging measures and clinical variables. Resting-state data were obtained from 46 male patients with untreated severe OSA and 46 male good sleepers (GSs). We specifically selected 20 DMN subregions to construct the DMN architecture. The disrupted FC and topological properties of the DMN in patients with OSA were characterized using graph theory. The OSA group showed significantly decreased FC of the anterior–posterior DMN and within the posterior DMN, and also showed increased FC within the DMN. The DMN exhibited small-world topology in both OSA and GS groups. Compared to GSs, patients with OSA showed a decreased clustering coefficient (Cp) and local efficiency, and decreased nodal centralities in the left posterior cingulate cortex and dorsal medial prefrontal cortex, and increased nodal centralities in the ventral medial prefrontal cortex and the right parahippocampal cortex. Finally, the abnormal DMN FC was significantly related to Cp, path length, global efficiency, and Montreal cognitive assessment score. OSA showed disrupted FC within the DMN, which may have contributed to the observed topological reorganization. These findings may provide further evidence of cognitive deficits in patients with OSA.

For the past decades, networked control systems (NCSs), as an interdisciplinary subject, have been one of the main research highlights and many fruitful results from different aspects have been achieved. With these growing research trends, it is significant to consolidate the latest knowledge and information to keep up with the research needs. In this paper, the results of different aspects of NCSs, such as quantization, estimation, fault detection and networked predictive control, are summarized. In addition, with the development of cloud technique, cloud control systems are proposed for the further development of NCSs.